Model Jaringan Syaraf Tiruan Dalam Memprediksi Produksi Susu Segar Di Indonesia Berdasarkan Propinsi

Rika Asma Dewi, Rusmansyah Rusmansyah, Syahrul Ramadan, Sundari Retno Andani, Solikhun Solikhun

Sari


The problem of drinking fresh milk in Indonesia looks minimal and rarely from children to adults who drink fresh milk, both milk and milk in canned milk. In an effort to realize the provisions as stipulated in the Minister of Health Regulation No. 75 of 2013 informing one's nutritional needs based on age and sex, the Indonesian Government has increased nutritional needs in Indonesia. This research contributes to the government to be able to predict the Production of Fresh Milk in Indonesia by Province. The data used is data from the National Statistics Agency through the website www.bps.go.id. The data is predictive data of fresh milk from 2010 to 2017. The algorithm used in this study is Artificial Neural Networks with the Backpropogation method. The input variables used were data for 2010 (X1), data for 2011 (X2), data for 2012 (X3), data for 2013 (X4), data for 2014 (X5), data for 2015 (X6) and 2016 data (X7) with 4 training and testing architectural models, namely 7-2-1, 7-4-1, 7-16-1 and 7-32-1. Target data is taken from 2017 data. The resulting output is the best pattern of Artificial Neural Network architecture. The best architectural model is 7-4-1 with EPOCH 1042, MSE 0.0095979 and 100% accuracy rate. From this model, the prediction of Fresh Milk Production is based on provinces in Indonesia.

Kata Kunci


Fresh Milk, ANN, Backpropogation and Prediction

Teks Lengkap:

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Referensi


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